Unmanned Aerial Vehicle Image Dehazing Algorithm Based on Simple Linear Iterative Clustering Optimization and Its Application in Wind Farm

Sha LIU; Zhe SUN; Zifeng QIU; Yan HU

doi:10.12096/j.2096-4528.pgt.20006

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Unmanned Aerial Vehicle Image Dehazing Algorithm Based on Simple Linear Iterative Clustering Optimization and Its Application in Wind Farm

New and Renewable Energy | 更新时间：2025-07-04

- Unmanned Aerial Vehicle Image Dehazing Algorithm Based on Simple Linear Iterative Clustering Optimization and Its Application in Wind Farm
- Power Generation Technology Vol. 41, Issue 6, Pages: 608-616(2020)
- 作者机构：
  
  1.中国电子科技集团公司第五十四研究所, 河北省石家庄市 050081
  2.海装驻邯郸地区军事代表室, 河北省石家庄市 050081
  3.中国电子科技集团公司航天信息应用技术重点实验室, 河北省石家庄市 050081
- 作者简介：
- 基金信息：
  
  National Key Research & Development Program of China(2017YFB0503003)
- DOI：10.12096/j.2096-4528.pgt.20006
  CLC： TK83;TP391.41
- Received：17 March 2020，
  
  Published：31 December 2020
- 稿件说明：
移动端阅览
Sha LIU, Zhe SUN, Zifeng QIU, et al. Unmanned Aerial Vehicle Image Dehazing Algorithm Based on Simple Linear Iterative Clustering Optimization and Its Application in Wind Farm[J]. Power Generation Technology, 2020, 41(6): 608-616.
DOI：

Sha LIU, Zhe SUN, Zifeng QIU, et al. Unmanned Aerial Vehicle Image Dehazing Algorithm Based on Simple Linear Iterative Clustering Optimization and Its Application in Wind Farm[J]. Power Generation Technology, 2020, 41(6): 608-616. DOI： 10.12096/j.2096-4528.pgt.20006.

摘要

针对电力巡检过程中无人机（unmanned aerial vehicle，UAV）载荷因受雾气颗粒影响而导致UAV图像不清晰的问题，提出一种基于简单线性迭代聚类（simple linear iterative clustering，SLIC）优化的UAV图像去雾算法。通过雾天成像物理模型、暗通道先验定律、同质滤波与SLIC算法，改善电力巡检图像中白色区域及不均匀光照的影响，提升UAV图像去雾处理的效率，并对大气光强度参数进行自适应计算，以防止去雾过程中复原失真。实验结果表明提出的算法可有效恢复电力巡检图像的原始细节，并通过主观视觉评估及融合多种客观评价指标的对比，说明该算法相对于传统算法的优越性。

Abstract

In order to solve the problem that the unmanned aerial vehicle (UAV) image is not clear due to the influence of fog particles

a UAV image dehazing algorithm based on simple linear iterative clustering (SLIC) optimization was proposed. Through the physical model of fog imaging

the prior law of dark channel

homogeneous filtering and SLIC algorithm

the influence of white area and uneven light in power inspection image was improved

the efficiency of UAV image dehazing was improved

and the adaptive calculation of atmospheric light intensity parameters was carried out to prevent the distortion in the dehazing process. The experimental results show that the algorithm can effectively restore the original details of the power inspection image. Through the comparison of subjective visual evaluation and fusion of a variety of objective evaluation indexes

it shows the superiority of the algorithm compared with the traditional algorithms.

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Keywords

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